What Is Serverless Computing?

With every new technology, the way we create and deliver applications is altered. The newest addition to cloud computing technologies is serverless computing. As the name itself explains, serverless computing does not indicate that servers no longer exist. It is actually a change in the paradigm of how we create, deploy, and execute applications.

With traditional computing models, developers either have to take on servers themselves or pay for providers to host infrastructure. The process of installing, scaling, and patching servers can be time and labor-intensive. Serverless computing frees them from that because developers only get to write code while the cloud provider has the luxury of doing server-side work behind the scenes.

Let’s deconstruct what serverless computing is, how it works, its pros, its cons, and why it’s so the cool thing for companies to do these days.

Understanding Serverless Computing

Basically, serverless computing is a cloud computing paradigm in which an underlying infrastructure is provisioned by a cloud provider for automatically executing applications. What this basically implies is that there is no need for developers to concern themselves with provisioning servers, keeping operating systems up and running, or even scaling problems.

Serverless programming separates code into brief, stateless functions that run in response to specific events. They exist independently and get invoked when they are required, and typically do so for a brief period, i.e., long enough to act or respond to an event. This service is commonly known as Function as a Service (FaaS).

For example, if there is an online shop and the user has clicked on “Buy Now” to buy a product. That click can trigger a serverless function to trigger payment processing. After payment, the function is stopped and there is no leftover resource running eating computation power in that process.

Major cloud providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud all have serverless platforms with some type of FaaS. Some of them include: Google Cloud Functions, Azure Functions, and AWS Lambda.

What is Serverless Computing?

How the serverless model achieves this is by decomposing applications into separate, small functions. Each function does some particular job, e.g., processing a form submission, image resizing, or API request processing. These standalone functions do not need a server to always run. Instead, they remain inactive until invoked.

When something happens—a file is uploaded by a user or a form is posted—the associated function is automatically invoked by the cloud provider. The provider employs computing resources for a fraction of a second to execute the function. Resources are returned when the function completes.

A brief rundown of what occurs:

1. Trigger/Event: Something happens—such as a web request, file upload, or database modification.
2. Function Call: The correct function is called, performs its job, and ends.
3. Resource Management: Resource provisioning and scaling are handled automatically by the cloud provider.
4. Billing: You simply pay for the compute time the function runs when it’s running—not for idle servers.

Because infrastructure is abstracted away from the programmer, applications are easier to write, faster to deploy, and less expensive to run.

Key Benefits of Serverless Computing

One of the most significant reasons why serverless computing is so widely popular all around the world is the numerous benefits that it can have for developers and companies. The following are Some of the benefits that stood out:

1. No Server Management

The developers are no longer required to be concerned about provisioning, setting up, and upgrading servers. From hardware provisioning to software patching, the cloud provider does everything, and teams simply code well.

2. Automatic Scaling

With traditional servers, typically ahead of time and configuring load balancers or auto-scaling groups to handle traffic spikes. Serverless computing adjusts automatically up or down based on demand. Whether your application handles ten requests or ten thousand, the platform responds.

3. Cost Efficiency

In traditional cloud models, you typically have to pay for the servers irrespective of their usage. You only pay for used computing capacity while a function runs in serverless systems. This “pay-as-you-go” aspect makes it a cost-effective model for start-ups, small enterprises, or bursty applications.

4. Faster Development and Deployment

As developers need not worry about infrastructure, they will be able to spend more time building features and creating better user experiences. Applications can be coded, tested, and deployed in infinitesimal increments and therefore updates and patches become immediate and convenient.

5. Improved Utilization of Resources

There are no servers to pre-book in serverless. The cloud provider provides the resources when necessary and uses them once the usage is finished. This offers improved utilization of resources without wastage.

Serverless Computing Applications

There is a vast array of applications that can make the most of serverless computing. Some of the most prevalent ones are:

1. Web Applications and APIs

Serverless functions are used by most web applications to power some form of functionality like authentication, file upload, or data processing. Serverless is also the best option to create thin APIs serving dynamic content to front-end apps.

2. Data Processing

Serverless functions can be triggered as events by uploading files into cloud storage. Serverless functions can process such files resize pictures, convert video, or check data before storing them elsewhere.

3. IoT (Internet of Things)

As IoT devices keep providing reports, serverless functions are ideal to handle little bursts of communication and real-time processing of the data.

4. Chatbots and Automation

Serverless platforms are also helpful in building chatbots or automated flows where functions respond to user commands or execute in the background without requiring full-fledged servers running all the time.

5. Scheduled Tasks

Operation such as posting reports every day, database backup, or purging old records can be performed as serverless functions that run only when needed.

Serverless Computing Problems

Although serverless computing has many benefits, it also has drawbacks. One should be aware of the model’s weaknesses.

1. Cold Starts

When the serverless function is first called after some time since the last call, there could be some slight delay called a “cold start.” Although most of the providers will make every effort to avoid this, cold starts can impact the responsiveness of applications that have requirements of real-time response.

2. Limited Execution Time

Most serverless platforms cap a function’s lifetime. If your application demands long-running actions or computationally intensive tasks, serverless would not be appropriate.

3. Vendor Lock-In

Building applications with heavy dependence on the specific provider’s serverless platform may make it difficult to change providers in the future. While attempts have been made at standardization, vendor lock-in remains something to bear in mind.

4. Complexity for Large Applications

For very large applications, hundreds or even dozens of small serverless functions may be adding new debugging, organizational, and monitoring issues.

5. Security Issues

Although most of the security of the underlying infrastructure will be the cloud provider’s problem, developers will continue to need to ensure that they use good security practices such as encrypting APIs, sanitizing user data, and using good access controls.

The Future of Serverless Computing

With more and more applications being developed as cloud-first, serverless computing must become even more ubiquitous. Tooling, monitoring, and portability between providers will address some of its present limitations. Hybrid models in which some of an app is serverless and some uses traditional servers or containers are now the standard. Serverless is gaining traction.

Additionally, the development of Edge Computing applications executed closer to the user is also pushing serverless capabilities to near end-users, reducing latency and improving app performance for applications across the world.

Serverless is gaining increasing popularity alongside other cloud-native technologies such as microservices and containers, providing a dynamic platform for development of next-generation apps.

Conclusion

A paradigm shift in software development and deployment is being brought about by serverless computing. With the infrastructure removed, developers can now code to solve business problems. The benefits—auto scale, cost-efficient, quick development, and no server maintenance are compelling reasons why most contemporary applications would be great candidates for serverless computing.

But serverless is not a cure-all. Some applications with stringent performance needs, with operations that take very long to run, or with highly interdependent relationships will need other solutions. Nevertheless, for most companies and developers, serverless offers new avenues for creating scalable, affordable, and innovative software.

With technology continuing to advance at an incredible pace, it’s clear that serverless computing will be one of the drivers of the future of app development. It enables developers to code smarter, deploy quicker, and run better without worrying about what is actually occurring in the background.